17 citations · 19 across the 5 of their papers we have counts for
5 papers
Retrieval-Confused Generation is a Good Defender for Privacy Violation Attack of Large Language Models
Wanli Peng, Xin Chen, Hang Fu +3
Recent advances in large language models (LLMs) have made a profound impact on our society and also raised new security concerns. Particularly, due to the remarkable inference abil…
BadApex: Backdoor Attack Based on Adaptive Optimization Mechanism of Black-box Large Language Models
Zhengxian Wu, Juan Wen, Wanli Peng +3
Previous insertion-based and paraphrase-based backdoors have achieved great success in attack efficacy, but they ignore the text quality and semantic consistency between poisoned a…
ImF: Implicit Fingerprint for Large Language Models
Jiaxuan Wu, Wanli Peng, Hang Fu +2
Training large language models (LLMs) is resource-intensive and expensive, making protecting intellectual property (IP) for LLMs crucial. Recently, embedding fingerprints into LLMs…
Generative Text Steganography with Large Language Model
Jiaxuan Wu, Zhengxian Wu, Yiming Xue +2
Recent advances in large language models (LLMs) have blurred the boundary of high-quality text generation between humans and machines, which is favorable for generative text stegan…
When Super-Resolution Meets Camouflaged Object Detection: A Comparison Study
Juan Wen, Shupeng Cheng, Peng Xu +4
Super Resolution (SR) and Camouflaged Object Detection (COD) are two hot topics in computer vision with various joint applications. For instance, low-resolution surveillance images…